Yingmin Jia
Invited Speaker

Yingmin Jia

Professor of Control Science and Engineering

School of Automation Science and Electrical Engineering
Beihang University, Beijing, China

ISCIIA 2026 · Beijing · October 30 – November 2, 2026
Beihang University Robust Control Adaptive Control Intelligent Control Machine Learning

Biography

Professor Yingmin Jia is a Professor and PhD Supervisor in the School of Automation Science and Electrical Engineering at Beihang University, Beijing, China. He received his B.S. degree in Control Theory from Shandong University in 1982, and his M.S. and Ph.D. degrees in Automatic Control Theory and Applications from Beihang University in 1990 and 1993, respectively. He subsequently completed postdoctoral research in aeronautics and astronautics at Beihang University.

His research covers robust and adaptive control, intelligent control, artificial life and machine learning, cross-scale control, and motion reproduction. His work also includes applications of advanced control methods to robotic systems, multi-agent systems, vehicle systems, and aerospace systems.

Professor Jia has received a number of major academic and scientific distinctions. He was supported by the National Science Fund for Distinguished Young Scholars in 1996, became a distinguished professor under the Chang Jiang Scholars Program in 2004, and was recognized as a National Excellent Postdoctoral Researcher in 2005. He later served as Chief Scientist of a National 973 Program project and led major national scientific instrumentation research projects.

Research Overview

Advanced Control, Intelligent Systems, and Aerospace Applications

Professor Jia's research centers on the theory and engineering applications of advanced control and intelligent systems. A major theme of his work is the development of robust and adaptive control methods for complex dynamic systems subject to uncertainty, nonlinear behavior, and demanding performance requirements.

His research also extends to intelligent control, machine learning, multi-agent coordination, robotics, and aerospace systems. These topics connect fundamental control theory with practical problems in autonomous systems, robotic platforms, distributed systems, and complex aerospace applications.

Robust and adaptive control of uncertain systems
Intelligent control and machine learning
Multi-agent and distributed control systems
Robotics and autonomous systems
Cross-scale control and motion reproduction
Aerospace and vehicle control applications

Research Interests

  • Robust Control
  • Adaptive Control
  • Intelligent Control
  • Artificial Life and Machine Learning
  • Multi-Agent Systems
  • Robotics and Autonomous Systems
  • Cross-Scale Control and Motion Reproduction
  • Aerospace System Control

Selected Distinctions

  • National Science Fund for Distinguished Young Scholars, 1996
  • Chang Jiang Scholars Program Distinguished Professor, 2004
  • National Excellent Postdoctoral Researcher, 2005
  • Chief Scientist, National 973 Program Project, 2011
  • National Technological Invention Award, Second Prize, 2015
  • Ministry of Education Natural Science Award, First Prize, 2017
  • Wu Wenjun AI Science and Technology Invention Award, First Prize, 2017
  • Fellow of the Chinese Association of Automation, 2019

Academic Profile

Academic Position
Professor and PhD Supervisor, School of Automation Science and Electrical Engineering, Beihang University
Discipline
Control Science and Engineering
Education
B.S., Shandong University, 1982; M.S., Beihang University, 1990; Ph.D., Beihang University, 1993
International Experience
Visiting research experience supported by DLR in Germany, the Alexander von Humboldt Foundation, the Japan Society for the Promotion of Science, and the China Scholarship Council
Research Focus
Robust and adaptive control, intelligent control, machine learning, multi-agent systems, robotics, and aerospace systems